The politics of allyship: Multiethnic coalitions and mass attitudes toward protest.

Recent work finds that nonviolent resistance by ethnic minorities is perceived as more violent and requiring more policing than identical resistance by ethnic majorities, reducing its impact and effectiveness. We ask whether allies-advantaged group participants in disadvantaged group movements-can mitigate these barriers. On the one hand, allies can counter negative stereotypes and defuse threat perceptions among advantaged group members, while raising expectations of success and lowering expected risks among disadvantaged group members. On the other hand, allies can entail significant costs, carrying risks of cooptation, replication of power hierarchies, and marginalization of core constituencies. To shed light on this question we draw on the case of the Black Lives Matter (BLM) movement, which, in 2020, attracted unprecedented White participation. Employing a national survey experiment, we find that sizeable White presence at racial justice protests increases protest approval, reduces perceptions of violence, and raises the likelihood of participation among White audiences, while not causing significant backlash among Black audiences. Black respondents mostly see White presence as useful for advancing the movement's goals, and predominant White presence reduces expectations that protests will be forcefully repressed. We complement these results with analysis of tens of thousands of images shared on social media during the 2020 BLM protests, finding a significant association between the presence of Whites in the images and user engagement and amplification. The findings suggest that allyship can be a powerful tool for promoting sociopolitical change amid deep structural inequality.

Machine-learning analysis of leadership formation in China to parse the roles of loyalty and institutional norms.

A thriving cottage industry has long tried to predict the selection outcomes of the Chinese leadership using qualitative judgments based on historical trends and elite interviews. This study contributes to the discourse by adopting machine-learning techniques to quantitatively and systematically evaluate the promotion prospects of Chinese high-ranking officials. By incorporating over 250 individual features of approximately 20,000 high-ranking positions from 1982 to 2020, this paper calculated predicted probabilities of promotion for the 19th Politburo members of the Communist Party of China. The rankings of the promotion probabilities can be used not only to identify candidates who would have traditionally advanced within the party's promotion norms but also to gauge Xi Jinping's personal favoritism toward specific individuals. Based on different specifications for positions and periods, we developed measurements to quantify candidates' levels of perceived loyalty and promotion eligibility. The empirical results demonstrated that the newly formed 20th Politburo Standing Committee was predominantly composed of loyalists who would not have risen to such positions under conventional promotion standards. We further found that, even within his circle of known allies, Xi Jinping did not opt for candidates with strong credentials. The findings of this study underscore the increasing emphasis on loyalty and the diminishing role of institutional norms in China's high-ranking selections.

Generically partisan: Polarization in political communication.

American political parties continue to grow more polarized, but the extent of ideological polarization among the public is much less than the extent of perceived polarization (what the ideological gap is believed to be). Perceived polarization is concerning because of its link to interparty hostility, but it remains unclear what drives this phenomenon. We propose that a tendency for individuals to form broad generalizations about groups on the basis of inconsistent evidence may be partly responsible. We study this tendency by measuring the interpretation, endorsement, and recall of category-referring statements, also known as generics (e.g., "Democrats favor affirmative action"). In study 1 (n = 417), perceived polarization was substantially greater than actual polarization. Further, participants endorsed generics as long as they were true more often of the target party (e.g., Democrats favor affirmative action) than of the opposing party (e.g., Republicans favor affirmative action), even when they believed such statements to be true for well below 50% of the relevant party. Study 2 (n = 928) found that upon receiving information from political elites, people tended to recall these statements as generic, regardless of whether the original statement was generic or not. Study 3 (n = 422) found that generic statements regarding new political information led to polarized judgments and did so more than nongeneric statements. Altogether, the data indicate a tendency toward holding mental representations of political claims that exaggerate party differences. These findings suggest that the use of generic language, common in everyday speech, enables inferential errors that exacerbate perceived polarization.